Institute of Bioanalytical Chemistry, Faculty of Chemistry and Mineralogy, University of Leipzig, Deutscher Platz 5, 04103, Leipzig, Germany.
Center for Biotechnology and Biomedicine, University of Leipzig, Deutscher Platz 5, 04103, Leipzig, Germany.
Anal Bioanal Chem. 2020 Jun;412(15):3573-3584. doi: 10.1007/s00216-020-02576-x. Epub 2020 Apr 2.
Lipidomics analysis for large-scale studies aiming at the identification and quantification of natural lipidomes is often performed using LC-MS-based data acquisition. However, the choice of suitable LC-MS method for accurate lipid quantification remains a matter of debate. Here, we performed the systematic comparison between two HRAM-MS-based quantification workflows based on HILIC and RPLC MS by quantifying 191 lipids from five lipid classes in human blood plasma using deuterated standards in the "one ISTD-per-lipid class" approach. Lipid quantification was performed considering all necessary isotopic corrections, and obtained correction factors are illustrated. Concentrations of lipids in NIST® SRM® 1950 human blood plasma determined by the two methods were comparable for most of the studied lipid species except for highly unsaturated phosphatidylcholines (PC). A comparison of lipid concentrations to consensus values determined in a previously published multi-laboratory study illustrated possible "overestimation" of concentrations for these highly unsaturated lipids by HILIC MS. We evaluated the influence of lipid loading amounts as well as the difference between quantified lipid and internal standard concentrations on the HILIC MS quantification results. We conclude that both HILIC and RPLC HRAM-MS workflows can be equally used for accurate lysophosphatidylcholine (LPC), lysophosphatidylethanolamine (LPE), phosphatidylcholine (PC), phosphatidylethanolamine (PE), and sphingomyelin (SM) lipid quantification, despite significant differences in the concentration of highly unsaturated PC lipids which need to be addressed by establishing response factors to account for the differences in degree of lipid unsaturation. Graphical.
针对天然脂质组学的鉴定和定量的大规模研究,通常使用基于 LC-MS 的数据采集进行脂质组学分析。然而,对于准确的脂质定量,合适的 LC-MS 方法的选择仍然存在争议。在这里,我们通过使用“一种内标物质对应一种脂质类别”的方法,在氘代标准品的辅助下,从人血浆中的五个脂质类别中定量了 191 种脂质,对基于亲水作用色谱(HILIC)和反相液相色谱(RPLC)的两种 HRAM-MS 定量工作流程进行了系统比较。考虑了所有必要的同位素校正,对脂质定量进行了校正因子的图示说明。两种方法对 NIST® SRM® 1950 人血浆中脂质的定量结果,除了高度不饱和的磷脂酰胆碱(PC)外,对于大多数研究的脂质种类都是可比的。将脂质浓度与之前发表的多实验室研究中确定的共识值进行比较,说明了 HILIC MS 对这些高度不饱和脂质的浓度可能存在“高估”。我们评估了脂质加载量以及定量脂质和内标浓度之间的差异对 HILIC MS 定量结果的影响。我们得出结论,尽管高度不饱和 PC 脂质的浓度存在显著差异,但 HILIC 和 RPLC HRAM-MS 工作流程都可以同等用于准确定量溶血磷脂酰胆碱(LPC)、溶血磷脂酰乙醇胺(LPE)、磷脂酰胆碱(PC)、磷脂酰乙醇胺(PE)和鞘磷脂(SM)脂质,需要通过建立响应因子来解决脂质不饱和程度的差异。图表。